I had the opportunity to speak and participate in a panel on data governance as it pertained to big data. My presentation was based on recently completed research sponsored by IBM to understand, what does data governance look like by firms embarking/executing on big data? The overarching theme was that data governance is about protect and serve. Manage security and privacy while delivering trusted data.

Yet, when you look at data governance and what it means to the data practice, not the technology, protect and serve is also a credo. In business terms it represents:

Protect the reputation and mitigate risk associated with inappropriate use or dirty data.

Serve information needs of the business to have information fast and stay agile to market conditions.

It seems simple, even to the point of having a "duh" moment, as my teenager would say. However, don't let simplicity mask the reality; this is a bit more nuanced.

In many discussions and company examples, IT organizations and the emerging offices of chief data officers still lean more to protect over serve. Governance still equals control. In fact, the very nature of ensuring that data governance ultimately succeeds or that the office gets anything done can often mean the need of a highly forceful dynamo to lead the charge. Authority to command is crucial. Hard decisions need to me made. In early stages, "no" is more often heard than "yes!" In the grand scheme of things for the enterprise, especially as a chief data officer, the responsibility is to executives. They need to trust the data. The controls and processes at an enterprise level are tailored to their needs and expectations of information. Yet, in the world of big data, empowerment of the business to outsource IT, the number of increasingly tech-savvy businesspeople, and the ability to serve creates a more faceted data strategy — in turn a multifaceted need for data governance.

One size fits all is old data governance. Data governance zones are today's manifesto.

Don't get me wrong; you need centralized oversight. You need executive commitment in the form of driving accountability and provisioning of resources to manage and govern data. However, the door is open and the business can get what they need from outside sources and partners without IT intervention or an executive sign-off. In fact, if governance slows things down and the reward outweighs the risk, sorry, data governance councils and IT data management is on the losing end of the argument.

In a big data era, the mission of data governance, and for chief data officers, has to be about catering to the speed, access, and education of business stakeholders to make good decisions about what to trust if they look outside of IT to support their data-driven initiatives. Just as IT has established policies to do things more efficiently and manage resource ratios across internal, offshore, and outsourced venues, so will the business. What data governance helps with is providing the framework and requirements that partners need to abide by, or that business stakeholders will use to vet the trustworthiness of data or services to be incorporated into their wider strategies.

This is as much about protect and serve as it is about governance data in zones in a multifaceted ecosystem: zones of data architecture, zones of data types, and zones of consumption. IT and the chief data officer rule architecture zones; the business rules the world of data types and consumption.

In the end, the difference of today's data governance in the world of big data is that protect and serve are equal. The voice of the business will not be stifled.